<p>
    Various time series forecasting models (SMA, EMA, etc.) have been applied to stocks to forecast price movements.
    More recently, with the advent of Neural Networks, which have seen applications in several fields, ranging from
    medicine to fraud detection, researchers have tried to apply Neural Networks to the markets in an attempt to forecast price
    movements. Convolutional Neural Networks (CNNs) are a class of Neural Networks most widely known for their use in
    image classification, and now, researchers are applying CNNs to extract patterns, also known as <em>features</em>, from times-series
    data to forecast future stock prices.
</p>
